Campus Units

Industrial and Manufacturing Systems Engineering, Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2014

Journal or Book Title

Computational Statistics & Data Analysis

Volume

71

First Page

520

Last Page

529

DOI

10.1016/j.csda.2013.02.004

Abstract

A variety of existing symmetric parametric models for 3-D rotations found in both statistical and materials science literatures are considered from the point of view of the “uniform-axis-random-spin” (UARS) construction. One-sample Bayes methods for non-informative priors are provided for all of these models and attractive frequentist properties for corresponding Bayes inference on the model parameters are confirmed. Taken together with earlier work, the broad efficacy of non-informative Bayes inference for symmetric distributions on 3-D rotations is conclusively demonstrated.

Comments

This is a manuscript of an article published as One-sample Bayes inference for existing symmetric distributions on 3-d rotations. Computational Statistics and Data Analysis, 2014, Vol. 71, pp. 520-529, DOI:10.1016/j.csda.2013.02.004. With Yu Qiu and Dan Nordman.

Rights

© 2014. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier, B.V.

Language

en

File Format

application/pdf

Published Version

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